On the behavior of information theoretic criteria for model order selection of InSAR signals corrupted by multiplicative noise

被引:20
作者
Gini, F [1 ]
Bordoni, F [1 ]
机构
[1] Univ Pisa, Dipartimento Ingn Informaz, I-56126 Pisa, Italy
关键词
model order estimation; information theoretic criteria; multiplicative noise; multicomponent signals; SAR interferometry; layover phenomenon;
D O I
10.1016/S0165-1684(02)00506-6
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper deals with the estimation of the number of components in a multibaseline interferometric synthetic aperture radar (InSAR) signal corrupted by multiplicative noise, in the presence of the layover phenomenon. The appearance of multiplicative noise, termed speckle in the radar jargon, makes this problem very atypical. In fact, all the approaches proposed in literature have been applied to constant amplitude sinusoidal signals. In particular, the information theoretic criteria (ITC) have been conceived to estimate the number of signal components embedded in additive white noise. In this case, the problem of model order selection is equivalent to the estimation of the multiplicity of the smallest eigenvalues of the data covariance matrix. In presence of multiplicative noise, the signal eigenvalues spectrum changes. Consequently, the classical ITC methods operates under model mismatch. Nevertheless, before to look for other ad hoc methods, which could be difficult to derive or too heavy to implement, it is reasonable from an engineering point of view to investigate how the classical ITC methods are robust to the presence of multiplicative noise. Performance of the various ITC methods are analysed and compared under different operational scenarios. The relationship between performance and the eigenvalues distribution of the true covariance matrix is also investigated. (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:1047 / 1063
页数:17
相关论文
共 33 条
[1]   NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].
AKAIKE, H .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) :716-723
[2]   ASYMPTOTIC THEORY FOR PRINCIPAL COMPONENT ANALYSIS [J].
ANDERSON, TW .
ANNALS OF MATHEMATICAL STATISTICS, 1963, 34 (01) :122-&
[3]  
BAI ZD, 1985, RATES CONVERGENCE FA, P84
[4]   Development of a statistical procedure for detecting the number of signals in a radar measurement [J].
Chen, P ;
Wicks, MC ;
Adve, RS .
IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION, 2001, 148 (04) :219-226
[5]   Estimation of the number of signals from features of the covariance matrix: A supervised approach [J].
Costa, P ;
Grouffaud, J ;
Larzabal, P ;
Clergeot, H .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1999, 47 (11) :3108-3115
[6]   Layover solution in multibaseline SAR interferometry [J].
Gini, F ;
Lombardini, F ;
Montanari, M .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2002, 38 (04) :1344-1356
[7]  
Henderson F. M., 1998, Principles and Applications of Imaging Radar. Manual of Remote Sensing
[8]   Nonlinear filtering methods for harmonic retrieval and model order selection in Gaussian and non-Gaussian noise [J].
Hilands, TW ;
Thomopoulos, SCA .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1997, 45 (04) :982-995
[9]  
Homer J, 1996, INT GEOSCI REMOTE SE, P796, DOI 10.1109/IGARSS.1996.516478
[10]   On the behavior of information theoretic criteria for model order selection [J].
Liavas, AP ;
Regalia, PA .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2001, 49 (08) :1689-1695